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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High-resolution mapping of spatial heterogeneity in ice wedge polygon geomorphology near Prudhoe Bay, Alaska

It is well known that microtopography associated with ice wedge polygons drives pronounced, meter-scale spatial gradients in hydrologic and ecological processes on the tundra. However, highresolution maps of polygonal geomorphology are rarely available, due to the complexity and subtlety of ice wedge polygon relief at landscape scales. Here we present a sub-meter resolution map of >106 discrete ice wedge polygons across a ~1200 km2 landscape, delineated within a lidar-derived digital elevation model. The delineation procedure relies on a convolutional neural network paired with a set of common image processing operations and permits explicit measurement of relative elevation at the center of each ice wedge polygon. The resulting map visualizes meter- to kilometer-scale spatial gradients in polygonal geomorphology across an extensive landscape with unprecedented detail. This high-resolution inventory of polygonal geomorphology provides rich spatial context for extrapolating observations of environmental processes across the landscape. The map also represents an extensive baseline dataset for quantifying contemporary land surface deformation (i.e., thermokarst) at the survey area, through future topographic surveys.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Arctic cyclones have become more intense and longer-lived over the past seven decades

Intense cyclones driving extreme Arctic weather and climate events have been more frequently observed during recent years, causing dramatic environmental and socioeconomic impacts. However, inconsistencies have emerged about long-term changes in Arctic cyclone activity. Here we analyze multiple reanalysis datasets covering a multidecadal period with improvements to the cyclone tracking algorithm and the integrated cyclone activity metric. The results indicate an intensification of Arctic cyclone activity over the last seven decades. There has been a long-term shift of the maximum cyclone counts from weaker to stronger cyclones and a pronounced lengthening of the duration of strong cyclones. Spatial analysis shows increased strong cyclone frequency over the Arctic, driven by enhanced lower troposphere baroclinicity, amplified winter jet stream waves over the subpolar North Atlantic, and a strengthened summer tropospheric vortex over the central Arctic. The stratospheric vortex has also intensified the tropospheric waves and vortex with distinct dynamics between winter and summer. Recently enhanced baroclinicity over large areas of the Arctic and midlatitudes suggests more complicated atmospheric dynamics than what is hypothesized with Arctic-amplification-induced decrease in meridional temperature gradients.

Atmospheric dynamics↗
DOE OSTI2024

Highly cascaded first-order fiber Bragg gratings in highly multimode optical fibers for distributed temperature sensing under harsh environment conditions

This study presents a pioneering technique for fabricating highly cascaded first-order fiber Bragg gratings (FBGs) using a femtosecond laser-assisted point-by-point inscription method in highly multimode optical fibers, specifically Sapphire crystalline fiber, and pure silica coreless fiber. Notably, it marks the first successful demonstration of a distributed array comprising 10 FBGs within highly multimode fibers. This achievement is facilitated by a high-power laser technique that yields larger reflectors characterized by a Gaussian intensity profile. These first-order FBGs offer various advantages, including enhanced reflectivity, reduced fabrication time, and simplified spectral characteristics, enhancing their accessibility for interpretation when contrasted with higher-order FBGs. In addition to that it encompasses a comprehensive analysis of the robustness and efficacy of these FBGs, with particular emphasis on their ability to endure extreme temperatures. These FBGs demonstrate an advantageous capability for localized multi-point temperature monitoring, reaching temperatures up to 1500°C with sapphire crystalline fiber and 1100°C with pure silica coreless fiber. This resilience makes them suitable for deployment in harsh environmental conditions. This innovative approach substantially broadens the potential applications of highly multimode optical fibers, particularly in the arena of sensing and communication, where challenges related to thermal gradients and harsh environments prevail. Furthermore, these groundbreaking first-order FBGs signify a substantial advancement in the realm of distributed temperature sensing, offering supreme capabilities for temperature monitoring and signal stability. As such, our work holds the promise of a substantial impact on industries and applications that demand unwavering reliability under extreme conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Recent Advances in Assessing Environmental Effects of Marine Renewable Energy Around the World

Marine renewable energy (MRE) is increasingly of interest to coastal nations as a source of renewable energy that can support climate change mitigation goals as well as provide secure locally-produced energy for coastal and island communities. MRE extracts power from tidal streams, waves, ocean currents, run of rivers, and gradients in the ocean, with specialized devices developed and tested for each energy resource. Alongside development of MRE technologies and systems, first in Europe and then in North America, Australia, Asia, and other regions, it has been universally recognized that there is also a need to examine potential effects on marine animals, habitats, ecosystem processes, local communities and other sea users, to ensure that the MRE industry can be developed in a responsible and sustainable manner. This paper looks at the status of assessment and monitoring for potential environmental effects associated with MRE projects around the world. Over 80 projects were identified worldwide as having been tested, demonstrated, or commercially deployed with associated environmental monitoring. Five of the projects that represent tidal stream, wave, and run of river projects are examined in more detail to determine the types of data and information collected for those projects, the outputs of the monitoring campaigns, and the actions taken as a result of the data collection and analysis. Recommendations are provided for standardization of the monitoring approaches, instruments, and analysis methods at MRE project sites worldwide.

marine renewable energy, environmental effects, ri↗
DOE OSTI2023

Modeling strategies and data needs for representing coastal wetland vegetation in land surface models

Vegetated coastal ecosystems sequester carbon rapidly relative to terrestrial ecosystems. Coastal wetlands are poorly represented in land surface models, but work is underway to improve process-based, predictive modeling of these ecosystems. Here, in this work, we identify guiding questions, potential simulations, and data needs to make progress in improving representation of vegetation in terrestrial–aquatic interfaces, with a focus on coastal and estuarine ecosystems. We synthesize relevant plant traits and environmental controls on vegetation that influence carbon cycling in coastal ecosystems. We propose that models include separate plant functional types (PFTs) for mangroves, graminoid salt marshes, and succulent salt marshes to adequately represent the variation in aboveground and belowground productivity between common coastal wetland vegetation types. We also discuss the drivers and carbon storage consequences of shifts in dominant PFTs. We suggest several potential approaches to represent the diversity in vegetation tolerance and adaptations to fluctuations in salinity and water level, which drive key gradients in coastal wetland ecosystems. Finally, we discuss data needs for parameterizing and evaluating model implementations of coastal wetland vegetation types and function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multirobot Collaborative Pursuit Target Robot by Improved MADDPG

Policy formulation is one of the main problems in multirobot systems, especially in multirobot pursuit-evasion scenarios, where both sparse rewards and random environment changes bring great difficulties to find better strategy. Existing multirobot decision-making methods mostly use environmental rewards to promote robots to complete the target task that cannot achieve good results. This paper proposes a multirobot pursuit method based on improved multiagent deep deterministic policy gradient (MADDPG), which solves the problem of sparse rewards in multirobot pursuit-evasion scenarios by combining the intrinsic reward and the external environment. The state similarity module based on the threshold constraint is as a part of the intrinsic reward signal output by the intrinsic curiosity module, which is used to balance overexploration and insufficient exploration, so that the agent can use the intrinsic reward more effectively to learn better strategies. The simulation experiment results show that the proposed method can improve the reward value of robots and the success rate of the pursuit task significantly. The intuitive change is obviously reflected in the real-time distance between the pursuer and the escapee, the pursuer using the improved algorithm for training can get closer to the escapee more quickly, and the average following distance also decreases.

Zhou, Xiao↗
DOE OSTI2026

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

Anions↗
DOE OSTI2022

Summary of Working Group 3: Laser and High-Gradient Structure-Based Acceleration

Accelerating particles at high gradients with high efficiencies is essential for reduction of size and cost of future accelerators for science and industry. This includes a future multi-TeV e+e- collider for particle, free-electron lasers for basic energy sciences and national security, industrial accelerators for energy and environmental applications, and accelerators for other applications. One way to achieve this is to use advanced externally-powered structures, both laser and RF driven. Working Group 3 (WG3) discussed novel accelerating structures with new geometries, new materials, frequencies from microwave to THz and optical spectrum, and operating conditions from room temperature to cryogenic. Presentations included recent advances in understanding RF breakdown and multipactor phenomena at different frequencies and materials, and other physics limitations to the accelerating gradient. Other relevant topics, such as developing high-gradient photoinjectors, high-efficiency RF power sources, and RF structures for a potential muon collider were discussed also. More details on each of the WG3 topics can be found in the articles published in these proceedings.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)

Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R 2 =0.63; N: R 2 =0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R 2 =0.67; N: R 2 =0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that the model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.

58 GEOSCIENCES↗
DOE OSTI2020

Thaw Transitions and Redox Conditions Drive Methane Oxidation in a Permafrost Peatland

Thawing permafrost, ground that has been frozen for 2 or more years, often results in wet conditions that promote the production of methane (CH 4 ). Methane is a greenhouse gas that is over 30 times more powerful than carbon dioxide at warming the atmosphere. Microorganisms called methanotrophs can consume a substantial portion of this CH 4 before it reaches the atmosphere, but the extent of this consumption is not well understood. Methanotrophs are affected by environmental conditions, such as oxygen availability, that change with permafrost thaw. We used laboratory experiments to measure how quickly methanotrophs consume CH 4 from sites within a permafrost peatland with little, intermediate, and full permafrost thaw. We found that CH 4 consumption increased as permafrost thawed and that sites transitioning between thaw stages had a different potential to consume CH 4 than intact and fully thawed sites. Methane consumption was also high in locations with low dissolved oxygen, which suggests that methanotrophs in these sites may tolerate low oxygen conditions in the field. We found that redox potential, a measurement that describes the tendency for a compound to be oxidized or reduced, was a strong predictor of CH 4 consumption in partially and fully thawed sites. Overall, these measurements highlight the potential for methanotrophs to mitigate CH 4 emissions in peatlands with thawing permafrost and provide new insights to modeling CH 4 dynamics across the full thaw gradient.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Microcoleus (Cyanobacteria) form watershed-wide populations without strong gradients in population structure

The relative importance of separation by distance and by environment to population genetic diversity can be conveniently tested in river networks, where these two drivers are often independently distributed over space. To evaluate the importance of dispersal and environmental conditions in shaping microbial population structures, we performed genome-resolved metagenomic analyses of benthic Microcoleus -dominated cyanobacterial mats collected in the Eel and Russian River networks (California, USA). The 64 Microcoleus genomes were clustered into three species that shared >96.5% average nucleotide identity (ANI). Most mats were dominated by one strain, but minor alleles within mats were often shared, even over large spatial distances (>300 km). Within the most common Microcoleus species, the ANI between the dominant strains within mats decreased with increasing spatial separation. However, over shorter spatial distances (tens of kilometres), mats from different subwatersheds had lower ANI than mats from the same subwatershed, suggesting that at shorter spatial distances environmental differences between subwatersheds in factors like canopy cover, conductivity, and mean annual temperature decreases ANI. Since mats in smaller creeks had similar levels of nucleotide diversity (π) as mats in larger downstream subwatersheds, within-mat genetic diversity does not appear to depend on the downstream accumulation of upstream-derived strains. The four-gamete test and sequence length bias suggest recombination occurs between almost all strains within each species, even between populations separated by large distances or living in different habitats. Overall, our results show that, despite some isolation by distance and environmental conditions, sufficient gene-flow occurs among cyanobacterial strains to prevent either driver from producing distinctive population structures across the watershed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Data from: "Colonisation of the alpine tundra by trees: alpine neighbours assist late-seral but not early-seral conifer seedlings"

This archive contains data used to support conclusions made in “Colonisation of the alpine tundra by trees: alpine neighbours assist late-seral but not early-seral conifer seedlings”, by Jabis et al., 2020. Data were collected in the alpine field location of the Alpine Treeline Warming Experiment (ATWE), on Niwot Ridge, in the Front Range of the Colorado Rocky Mountains, USA.This package includes survivorship and physiology data for limber pine (Pinus flexilis), Engelmann spruce (Picea engelmannii), and Rocky Mountain snowlover (Chionophila jamesii). Site climate data such as soil moisture and temperature are also included. This data package contains ten comma-separated-values (.csv) files, and two rich-text-format (.rtf) files all compressed within one folder named “Neighbor_data_repository.zip”. Both file types can be opened by text-edit softwares such as TextEdit (Mac) and Notepad (Windows). The files are also compatible with analyses softwares such as R. .csv files can also be opened by Microsoft Excel. Two geospatial datasets are also included in this archive: one keyhole markup language (.kml) file with four points marking the corners of the study site, and a compressed file containing two ESRI shapefiles (.shp). The .kml files can be opened with Google Earth or Google Maps, and the shapefiles can be opened using any geographic information system applications, including the entire ArcGIS suite, and QGIS. -------------------------------------------------------------------------------------------------------------------------------------------------------The elevation mountain treeline is expected to shift upward with climate warming, and seed germination and seedling survival are critical local controls on treeline expansion. Neighboring alpine plants, either through competition for resources or through altering the microclimate, can also affect seedling emergence and survival. We asked whether establishing tree seedlings and an alpine herb are similarly sensitive to alpine plant neighbours under ambient and altered climate. We imposed active heating, watering, and neighbor removal experiments for emerging conifer seedlings and an alpine herb.We compared target plant survival, photosynthetic efficiency, and water use efficiency under ambient and experimental conditions. Picea engelmannii seedlings showed lower survival compared with Pinus flexilis three weeks following neighbour removal, and after 1 year only survived in watered plots. Pinus seedlings responded to neighbour removal by lowering the quantum yield of photosynthesis (ϕPSII). Contrary to expectations from the stress gradient hypothesis, survival was reduced without neighbours near the low-elevation range limit of Chionophila jamesii.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

WHONDRS Surface Water Chemistry and Organic Matter Characterization along the St. Lawrence River's Inland to Coastal Gradient, Eastern North America (v2)

This dataset supports a broader study examining the inland (Lake Ontario) to coastal (North Atlantic Ocean) geochemistry gradient along the St. Lawrence River in Canada and the United States. The St. Lawrence River is unique in that it contains the convergence of multiple water masses with distinct water signatures that mix only slightly as the river flows downstream. The dataset provides dissolved organic carbon (DOC) and organic matter characterization data generated from surface water. Samples were collected by researchers on board the Lampsilis research vessel (l’Université du Québec à Trois-Rivières) and small boats (St. Lawrence River Institute of Environmental Sciences, Cornwall) at 94 locations across and along the St. Lawrence River to capture longitudinal and transverse variation. Related data were collected and will be published separately in collaboration with the MicrEAU Laboratory (François Guillemette; l’Université du Québec à Trois-Rivières) and the Exploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) program. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (5) surface water sampling protocol; (6) readme; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; and (9) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. The data package was originally published in November 202. It was updated in April 2025 (v2; modified files). See the change history section in the readme for details.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Identifying snowfall elevation patterns by assimilating satellite-based snow depth retrievals

Precipitation in mountain regions is highly variable and poorly measured, posing important challenges to water resource management. Traditional methods to estimate precipitation include in-situ gauges, Doppler weather radars, satellite radars and radiometers, numerical modeling and reanalysis products. Each of these methods is unable to adequately capture complex orographic precipitation. Here, we propose a novel approach to characterize orographic snowfall over mountain regions. We use a particle batch smoother to leverage satellite information from Sentinel-1 derived snow depth retrievals and to correct various gridded precipitation products. This novel approach is tested using a simple snow model for an alpine basin located in Trentino Alto Adige, Italy. Here, we quantify the precipitation biases across the basin and found that the assimilation method (i) corrects for snowfall biases and uncertainties, (ii) leads to cumulative snowfall elevation patterns that are consistent across precipitation products, and (iii) results in overall improved basin-wide snow variables (snow depth and snow cover area) and basin streamflow estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impact of Cloud Longwave Scattering on Radiative Fluxes Associated With the Madden-Julian Oscillation in the Indian Ocean and Maritime Continent

Previous studies suggested that cloud longwave radiation contributes to the development and maintenance of the Madden-Julian Oscillation (MJO) and model-based convection is highly sensitive to the radiation scheme. However, currently used radiation schemes do not take cloud longwave scattering into account, resulting in an overestimation of the outgoing longwave radiation (OLR) and an underestimation of the downward longwave flux at the surface. We use combined active and passive satellite cloud property retrievals to quantify the one-layer cloud OLR and heating rate (HR) biases introduced by neglecting cloud longwave scattering in the Indian Ocean and Maritime Continent in the context of MJO, with a focus on its phases 3, 5, and 6. Here, the results show that the satellite-detected one-layer cloud area consists primarily of ice clouds, particularly during the boreal winter in the 4-year study period. An increased ice cloud area fraction of one-layer cloud groups is present up to 5 days before the onset of MJO events. If longwave scattering is neglected, the composite mean OLR overestimation over the one-layer ice cloud area from 5 days before to 4 days after the MJO passage is approximately 3.5 to 5.0 W m –2 . Neglecting longwave scattering also leads to a HR underestimation at cloud base and an overestimation at cloud top, making the base-to-top heating gradient less sharp at the cloud-resolving scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Mycorrhizal nutrient acquisition strategies shape tree competition and coexistence dynamics

Mycorrhizal fungi with different nutrient acquisition strategies influence plant species performance and physiology, thereby defining their trophic niche. This might drive resource competition dynamics that cumulatively impact tree species coexistence, but few manipulative experiments have directly tested this. Combining surveys and experiments in a modern coexistence theory framework, we tested how variation in mycorrhizal strategies and nutrient conditions affects plant competitive outcomes. We focused on two genera of co-occurring tree species with different mycorrhizal states: Acer (arbuscular mycorrhizal, AM) and Populus (dual mycorrhizal, but often considered predominantly ectomycorrhizal, EM). The EM and AM fungal responsiveness in Populus species varied with latitude and nitrogen (N) limitation. Host-specific soil microbiome conditioning and inorganic N fertilization combined to qualitatively affect coexistence outcomes. Lower N conditions favoured Populus over Acer trees, and N fertilization reversed this outcome for southern species, aligning with regional-scale forest mycorrhizal transitions. Results from the coexistence experiment also predict competitive exclusion between the tree species pairs, which could arise, in part, from their mycorrhizal differences and is consistent with alternative stable states in dominant forest mycorrhizal strategies. Such bistability appears in natural systems as a bimodal distribution of Populus vs. Acer tree species dominance using long-term forest inventory data. Synthesis: The magnitude and outcome of microbially mediated competition between Populus and Acer depends on soil nutrient availability, which likely relates to their mycorrhizal differentiation. These findings support the importance of mycorrhizal symbioses for contributing to large-scale biogeographical patterns of tree species trophic niche separation across soil resource gradients and bistability in forest mycorrhizal structure.

54 ENVIRONMENTAL SCIENCES↗